Sistem Peringatan Dini Kecepatan Angin Menggunakan Metode Kalman Filter Berbasis SMS

Abstract

This study presents the design and implementation of an early warning system for wind speed using the Kalman Filter method and Short Message Service (SMS) for real-time data transmission. The system is developed as a solution to the limited access to internet-based warning systems in coastal and remote areas. Wind speed is measured using a cup-type anemometer, while the DHT11 sensor monitors temperature. Data readings are processed by an Arduino Uno microcontroller and transmitted via the SIM800L GSM module in SMS format, enabling use on standard mobile devices with 2G networks. The Kalman Filter algorithm is applied to reduce noise caused by unstable wind, vegetation movement, or small animal interference. The system classifies wind speed into three levels: Safe (≤3.3 m/s), Alert (>3.3–8.1 m/s), and Danger (>8.1 m/s), with notifications via SMS and colored LED displays. Testing covered sensor accuracy, Kalman Filter performance, SMS delay, and overall system reliability. Results show measurement errors below 1% and SMS delays rated “excellent” by TIPHON standards. This system offers a reliable, low-cost solution for disaster risk reduction in internet-limited regions and can be further developed for broader early warning applications.